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Dr. Ahmed Z. Afify :: Publications:

Title:
Bayesian and classical inference under type-II censored samples of the extended inverse Gompertz distribution with engineering applications.
Authors: Elshahhat, A., Aljohani, H. M. and Afify, A. Z.
Year: 2021
Keywords: Not Available
Journal: Entropy
Volume: 23
Issue: Not Available
Pages: 1578
Publisher: Not Available
Local/International: International
Paper Link:
Full paper Not Available
Supplementary materials Not Available
Abstract:

In this article, we introduce a new three-parameter distribution called the extended inverse-Gompertz (EIGo) distribution. The implementation of three parameters provides a good reconstruction for some applications. The EIGo distribution can be seen as an extension of the inverted exponential, inverse Gompertz, and generalized inverted exponential distributions. Its failure rate function has an upside-down bathtub shape. Various statistical and reliability properties of the EIGo distribution are discussed. The model parameters are estimated by the maximum-likelihood and Bayesian methods under Type-II censored samples, where the parameters are explained using gamma priors. The performance of the proposed approaches is examined using simulation results. Finally, two real-life engineering data sets are analyzed to illustrate the applicability of the EIGo distribution, showing that it provides better fits than competing inverted models such as inverse-Gompertz, inverse-Weibull, inverse-gamma, generalized inverse-Weibull, exponentiated inverted-Weibull, generalized inverted half-logistic, inverted-Kumaraswamy, inverted Nadarajah–Haghighi, and alpha-power inverse-Weibull distributions.

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